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Article ; Online: Multitissue Multiomics Systems Biology to Dissect Complex Diseases.

Yang, Xia

2020 Volume 26, Issue 8, Page(s) 718–728

Abstract: Most complex diseases involve genetic and environmental risk factors, engage multiple cells and tissues, and follow a polygenic or omnigenic model depicting numerous genes contributing to pathophysiology. These multidimensional complexities pose ... ...

Abstract	Most complex diseases involve genetic and environmental risk factors, engage multiple cells and tissues, and follow a polygenic or omnigenic model depicting numerous genes contributing to pathophysiology. These multidimensional complexities pose challenges to traditional approaches that examine individual factors. In turn, multitissue multiomics systems biology has emerged to comprehensively elucidate within- and cross-tissue molecular networks underlying gene-by-environment interactions and contributing to complex diseases. The power of systems biology in retrieving novel insights and formulating new hypotheses has been well documented. However, the field faces various challenges that call for debate and action. In this opinion article, I discuss the concepts, benefits, current state, and challenges of the field and point to the next steps toward network-based systems medicine.
MeSH term(s)	Animals ; Computational Biology/methods ; Gene-Environment Interaction ; Genes/genetics ; Genomics/methods ; Humans ; Systems Biology/methods
Language	English
Publishing date	2020-05-18
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	2036490-8
ISSN	1471-499X ; 1471-4914
ISSN (online)	1471-499X
ISSN	1471-4914
DOI	10.1016/j.molmed.2020.04.006
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Article ; Online: Association between cerebrospinal fluid pressure and cognition in patients with Alzheimer's disease and Lewy body dementia.

Yang, Xia / Gan, Jinghuan / Ji, Yong

BMC neurology

2024 Volume 24, Issue 1, Page(s) 35

Abstract: Background: The relationship between cerebrospinal fluid pressure (CSFP) and cognition has received little research attention. The purpose of this study was to explore the relationship between CSFP and cognition in patients with Alzheimer's disease (AD) ...

Abstract	Background: The relationship between cerebrospinal fluid pressure (CSFP) and cognition has received little research attention. The purpose of this study was to explore the relationship between CSFP and cognition in patients with Alzheimer's disease (AD) and patients with Lewy body dementia (LBD). Method: We included 178 participants, including 137 patients with AD and 41 patients with LBD (including dementia with Lewy bodies (DLBs) and Parkinson's disease dementia (PDD)). CSFP was measured by lumbar puncture, and a patient-reported history and laboratory test data were collected. Logistic and linear regression analyses were used to evaluate the associations between CSFP and cognition, the cerebrospinal fluid (CSF) / serum albumin ratio (Qalb), and CSF biomarkers of AD. Results: The mean age of the included patients was 63.58 ± 8.77 years old, and the mean CSFP was 121 ± 33.72 mmH2O. A total of 76.9% of the patients had a CSFP distribution of [90-170) mmH2O, 46 patients (25.8%) had severe dementia, 83 patients (46.6%) had moderate dementia, 28 patients (15.7%) had mild dementia, and 21 patients (11.8%) had mild cognitive impairment (MCI) (including 16 patients with MCI due to AD and 5 patients with MCI due to LBD). In all patients (p value < 0.001) and in patients with AD (p value = 0.01), the mean cerebrospinal fluid pressure (CSFP) was higher in patients with MCI than in patients with dementia. In multivariate analysis, in all patients (OR: 6.37, 95% confidential interval (CI): 1.76-23.04, p = 0.005) and patients with AD (odds ratio (OR): 5.43, 95% CI: 1.41-20.87, p = 0.005), a CSFP in the lowest quartile ([50-90) mmH2O) was associated with a higher level of severe dementia than a CSFP in the highest quartile ([170-210) mmH2O). In addition, there was a significant linear correlation between CSFP and the Mini-Mental State Examination (MMSE) score in all patients with dementia (r = 0.43, p = 0.04, Durbin-Watson test (D-W test) = 0.75). Conclusion: In patients with AD, the mean cerebrospinal fluid pressure was higher in patients with MCI than in patients with dementia, and the decrease in CSFP was related to a more serious dementia level. However, no such relationship was found in patients with LBD.
MeSH term(s)	Humans ; Middle Aged ; Aged ; Alzheimer Disease/cerebrospinal fluid ; Dementia/complications ; Lewy Body Disease/complications ; tau Proteins/cerebrospinal fluid ; Parkinson Disease/complications ; Cognition ; Cognitive Dysfunction/diagnosis ; Biomarkers/cerebrospinal fluid ; Cerebrospinal Fluid Pressure ; Amyloid beta-Peptides/cerebrospinal fluid
Chemical Substances	tau Proteins ; Biomarkers ; Amyloid beta-Peptides
Language	English
Publishing date	2024-01-19
Publishing country	England
Document type	Journal Article
ZDB-ID	2041347-6
ISSN	1471-2377 ; 1471-2377
ISSN (online)	1471-2377
ISSN	1471-2377
DOI	10.1186/s12883-023-03502-1
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Article: [Role of mitophagy in diabetes mellitus and its complications and traditional Chinese medicine intervention: a review].

Fan, Li-Hui / Yang, Xia / Wang, Zhi-Gang

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica

2024 Volume 49, Issue 1, Page(s) 46–54

Abstract: Diabetes mellitus(DM) is a chronic endocrine disease characterized by hyperglycemia caused by carbohydrate or lipid metabolism disorders or insulin dysfunction. Hyperglycemia and long-term metabolic disorders in DM can damage tissues and organs ... ...

Abstract	Diabetes mellitus(DM) is a chronic endocrine disease characterized by hyperglycemia caused by carbohydrate or lipid metabolism disorders or insulin dysfunction. Hyperglycemia and long-term metabolic disorders in DM can damage tissues and organs throughout the body, leading to serious complications. Mitochondrial autophagy(mitophagy) is an important mitochondrial quality control process in cells and a special autophagy phenomenon, in which damaged or redundant mitochondria can be selectively removed by autophagic lysosome, which is crucial to maintain cell stability and survival under stress. Studies have confirmed that changes in autophagy play a role in the development and control of DM and its complications. Mitophagy has become a research hotspot in recent years and it is closely associated with the pathogenesis of a variety of diseases. Substantial evidence suggests that mitophagy plays a crucial role in regulating the metabolic homeostasis in the case of DM and its complications. Because the destructive great vessel complications and microvascular complications cause increased mortality, blindness, renal failure, and declined quality of life of DM patients, it is urgent to develop targeted therapies to intervene in DM and its complications. Traditional Chinese medicine(TCM), with a multi-component, multi-target, and multi-level action manner, can prevent the development of drug resistance and have significant therapeutic effects in the prevention and treatment of DM and its complications. Therefore, exploring the mechanisms of TCM in regulating mito-phagy may become a new method for treating DM and its complications. With focus on the roles and mechanisms of mitophagy in DM and its complications, this paper summarizes and prospects the research on the treatment of DM and its complications with TCM via re-gulating mitophagy, aiming to provide new ideas for the clinical practice.
MeSH term(s)	Humans ; Mitophagy/physiology ; Medicine, Chinese Traditional ; Quality of Life ; Diabetes Mellitus/drug therapy ; Diabetes Mellitus/genetics ; Hyperglycemia
Language	Chinese
Publishing date	2024-02-25
Publishing country	China
Document type	Review ; English Abstract ; Journal Article
ZDB-ID	1004649-5
ISSN	1001-5302 ; 0254-0029
ISSN	1001-5302 ; 0254-0029
DOI	10.19540/j.cnki.cjcmm.20230809.702
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Article ; Online: Causal roles of serum uric acid levels and gout in sepsis: a Mendelian randomization study.

Qin, Yujun / Yang, Xia / Ning, Zong

Shock (Augusta, Ga.)

2024

Abstract: Objective: Several epidemiological studies have identified a potential link between serum uric acid(UA), gout and sepsis. The primary objective of this study is to delve deeper into this connection, investigating the causal effect of UA and gout on ... ...

Abstract	Objective: Several epidemiological studies have identified a potential link between serum uric acid(UA), gout and sepsis. The primary objective of this study is to delve deeper into this connection, investigating the causal effect of UA and gout on sepsis by applying Mendelian Randomization (MR). Methods: The causal relationship was analyzed using data from genome-wide association study(GWAS). Inverse variance weighting (IVW) was used as the main analysis method. Three complementary methods were used for our MR analysis, which included the MR-Egger regression method, the weighted median method, the simple median method. Horizontal pleiotropy was identified by MR-Egger intercept test. Cochran's Q statistics were employed to assess the existence of instrument heterogeneity. The leave-one-out method was used as a sensitivity analysis. Results: The IVW results indicated that there was a positive causal relationship between UA and sepsis(critical care) (OR = 0.24, 95%CI: 0.04 to 0.43, P = 0.018, F = 4291.20). There was no significant association between UA and sepsis(28 day death in critical care) (OR = 0.10, 95%CI: -0.29 to 0.50, P = 0.604). There was no significant association between gout and sepsis(critical care) (OR = 0.85, 95%CI: -4.87 to 6.57, P = 0.771), and sepsis(28 day death in critical care) (OR = -6.30, 95%CI: -17.41 to 4.81, P = 0.267). Horizontal pleiotropy was absent in this study. The results were robust under all sensitivity analyses. Conclusion: The study revealed that elevated UA levels was causally linked with sepsis(critical care). No causal relationship had been found between UA and sepsis(28 day death in critical care), as well as between gout and sepsis.
Language	English
Publishing date	2024-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	1185432-7
ISSN	1540-0514 ; 1073-2322
ISSN (online)	1540-0514
ISSN	1073-2322
DOI	10.1097/SHK.0000000000002365
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Article ; Online: Causal roles of educational duration in bone mineral density and risk factors for osteoporosis: a Mendelian randomization study.

Qin, Yujun / Yang, Xia / Ning, Zong

BMC musculoskeletal disorders

2024 Volume 25, Issue 1, Page(s) 345

Abstract: Background: Educational duration might play a vital role in preventing the occurrence and development of osteoporosis(OP).: Purpose: To assess the causal effect of educational duration on bone mineral density(BMD) and risk factors for OP by Mendelian ...

Abstract	Background: Educational duration might play a vital role in preventing the occurrence and development of osteoporosis(OP). Purpose: To assess the causal effect of educational duration on bone mineral density(BMD) and risk factors for OP by Mendelian randomization(MR) study. Methods: The causal relationship was analyzed using data from genome-wide association study(GWAS). Inverse variance weighting (IVW) was used as the main analysis method. Horizontal pleiotropy was identified by MR-Egger intercept test, MR pleiotropy residual sum and outlier (MR-PRESSO) test. The leave-one-out method was used as a sensitivity analysis. Results: The IVW results indicated that there was a positive causal relationship between educational duration and BMD (OR = 1.012, 95%CI:1.003-1.022), physical activity(PA) (OR = 1.156, 95%CI:1.032-1.295), calcium consumption (OR = 1.004, 95%CI:1.002-1.005), and coffee intake (OR = 1.019, 95%CI:1.014-1.024). There was a negative association between whole body fat mass (OR = 0.950, 95%CI:0.939-0.961), time for vigorous PA (OR = 0.955, 95%CI:0.939-0.972), sunbath (OR = 0.987, 95%CI:0.986-0.989), salt consumption (OR = 0.965, 95%CI:0.959-0.971), fizzy drink intake (OR = 0.985, 95%CI:0.978-0.992), smoking (OR = 0.969, 95%CI:0.964-0.975), and falling risk (OR = 0.976, 95%CI:0.965-0.987). There was no significant association between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol intake. Horizontal pleiotropy was absent in this study. The results were robust under sensitivity analyses. Conclusion: A longer educational duration was causally linked with increased BMD. No causal relationship had been found between educational duration and lean mass, time for light-to-moderate PA, milk intake, and alcohol consumption as risk factors for osteoporosis.
MeSH term(s)	Humans ; Bone Density ; Mendelian Randomization Analysis ; Osteoporosis/epidemiology ; Osteoporosis/etiology ; Osteoporosis/genetics ; Risk Factors ; Exercise ; Genome-Wide Association Study ; Educational Status ; Time Factors ; Female
Language	English
Publishing date	2024-05-02
Publishing country	England
Document type	Journal Article
ZDB-ID	2041355-5
ISSN	1471-2474 ; 1471-2474
ISSN (online)	1471-2474
ISSN	1471-2474
DOI	10.1186/s12891-024-07428-8
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Article ; Online: Landslide Susceptibility Mapping Based on Multitemporal Remote Sensing Image Change Detection and Multiexponential Band Math

Xianyu Yu / Yang Xia / Jianguo Zhou / Weiwei Jiang

Sustainability, Vol 15, Iss 2226, p

2023 Volume 2226

Abstract: Landslides pose a great threat to the safety of people’s lives and property within disaster areas. In this study, the Zigui to Badong section of the Three Gorges Reservoir is used as the study area, and the land use (LU), land use change (LUC) and band ... ...

Abstract	Landslides pose a great threat to the safety of people’s lives and property within disaster areas. In this study, the Zigui to Badong section of the Three Gorges Reservoir is used as the study area, and the land use (LU), land use change (LUC) and band math (band) factors from 2016–2020 along with six selected commonly used factors are used to form a land use factor combination (LUFC), land use change factor combination (LUCFC) and band math factor combination (BMFC). An artificial neural network (ANN), a support vector machine (SVM) and a convolutional neural network (CNN) are chosen as the three models for landslide susceptibility mapping (LSM). The results show that the BMFC is generally better than the LUFC and the LUCFC. For the validation set, the highest simple ranking scores for the three models were obtained for the BMFC (37.2, 32.8 and 39.2), followed by the LUFC (28, 26.6 and 31.8) and the LUCFC (26.8, 28.6 and 20); that is, the band-based predictions are better than those based on the LU and LUC, and the CNN model provides the best prediction ability. According to the four groups of experimental results with ANNs, compared with LU and LUC, band is easier to access, yields higher predictive performance, and provides stronger stability. Thus, band can replace LU and LUC to a certain extent and provide support for automatic and real-time landslide monitoring.
Keywords	landslide susceptibility mapping (LSM) ; land use/land use change (LU/LUC) factors ; band math (band) factor ; artificial neural network (ANN) ; support vector machine (SVM) ; convolutional neural network (CNN) ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A novel traffic optimization method using GRU based deep neural network for the IoV system

Wu Wen / Dongliang Xu / Yang Xia

PeerJ Computer Science, Vol 9, p e

2023 Volume 1411

Abstract: At present, China is moving towards the direction of “Industry 4.0”. The development of the automobile industry, especially intelligent automobiles, is in full swing, which brings great convenience to people’s life and travel. However, at the same time, ... ...

Abstract	At present, China is moving towards the direction of “Industry 4.0”. The development of the automobile industry, especially intelligent automobiles, is in full swing, which brings great convenience to people’s life and travel. However, at the same time, urban traffic pressure is also increasingly prominent, and the situation of traffic congestion and traffic safety is not optimistic. In this context, the Internet of Vehicles (also known as “IoV”) opens up a new way to relieve urban traffic pressure. Therefore, in order to further optimize the road network traffic conditions in the IoV environment, this research focuses on the traffic flow prediction algorithm on the basis of deep learning to enhance traffic efficiency and safety. First, the study investigates the short-time traffic flow prediction by combining the characteristics of the IoV environment. To address the issues that existing algorithms cannot automatically extract data features and the model expression capability is weak, the study chooses to build a deep neural network using GRU model in deep learning for short-time traffic flow prediction, thereby improving the prediction accuracy of algorithm. Secondly, a fine-grained traffic flow statistics approach suitable for the IoV situation is suggested in accordance with the deep learning model that was built. The algorithm sends the vehicle characteristic data obtained through GRU model training into the fine-grained traffic flow statistics algorithm, so as to realize the statistics of traffic information of various types of vehicles. The advantage of this algorithm is that it can well count the traffic flow of multiple lanes, so as to better predict the current traffic status and achieve traffic optimization. Finally, the IoV environment is constructed to confirm the effectiveness of the prediction model. The prediction results prove that the new algorithm has good performance in traffic flow statistics in different scenarios.
Keywords	Road network traffic ; Internet of vehicles ; Deep learning ; GRU ; Traffic optimization ; Traffic flow prediction ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	380
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
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Article ; Online: Correction

Xianyu Yu / Yang Xia / Jianguo Zhou / Weiwei Jiang

Sustainability, Vol 15, Iss 9654, p

Yu et al. Landslide Susceptibility Mapping Based on Multitemporal Remote Sensing Image Change Detection and Multiexponential Band Math. Sustainability 2023, 15 , 2226

2023 Volume 9654

Abstract: The authors would like to make the following corrections about the published paper [.] ...

Abstract	The authors would like to make the following corrections about the published paper [.]
Keywords	n/a ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Truck-Drone Pickup and Delivery Problem with Drone Weight-Related Cost

Yang Xia / Tingying Wu / Beixin Xia / Junkang Zhang

Sustainability, Vol 15, Iss 23, p

2023 Volume 16342

Abstract: Truck-drone delivery is widely used in logistics distribution for achieving sustainable development, in which drone weight greatly affects transportation cost. Thus, we consider a new combined truck-drone pickup and delivery problem with drone weight- ... ...

Abstract	Truck-drone delivery is widely used in logistics distribution for achieving sustainable development, in which drone weight greatly affects transportation cost. Thus, we consider a new combined truck-drone pickup and delivery problem with drone weight-related cost in the context of last-mile logistics. A system of integer programming is formulated with the objective of minimizing the total cost of the drone weight-related cost, fixed vehicle cost and travel distance cost. An improved adaptive large neighborhood search algorithm (IALNS) is designed based on the characteristics of the problem, several effective destroy and repair operators are designed to explore the solution space, and a simulated annealing strategy is introduced to avoid falling into the local optimal solution. To evaluate the performance of the IALNS algorithm, 72 instances are randomly generated and tested. The computational results on small instances show that the proposed IALNS algorithm performs better than CPLEX both in efficiency and effectiveness. When comparing the truck-drone pickup and delivery problem with drone weight-related cost to the problem without drone weight-related cost, it is found that ignoring the drone weight constraints leads to an underestimate of the total travel cost by 12.61% based on the test of large instances.
Keywords	truck-drone pickup and delivery problem ; drone weight-related cost ; adaptive large neighborhood search algorithm ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	006
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Chitosan interaction with stomach mucin layer to enhances gastric retention and mucoadhesive properties.

Ahmad, Khurshid / Zhang, Yanying / Chen, Peng / Yang, Xia / Hou, Hu

Carbohydrate polymers

2024 Volume 333, Page(s) 121926

Abstract: The interaction between mucoadhesive materials and mucin layers is of significant interest in the development of drug delivery systems and biomedical applications for effective targeting and prolonged stay in the gastrointestinal tract. In this article, ... ...

Abstract	The interaction between mucoadhesive materials and mucin layers is of significant interest in the development of drug delivery systems and biomedical applications for effective targeting and prolonged stay in the gastrointestinal tract. In this article, the current advancement and mucoadhesive properties of chitosan concerning the stomach mucin layer and its interactions have been briefly addressed. Chitosan a biocompatible polysaccharide exhibited promising mucoadhesive properties attributed to its cationic nature and ability to establish bonds with mucin glycoproteins. The mucoadhesion mechanism is ascribed to the electrostatic interactions between the positively charged amino (NH
MeSH term(s)	Gastric Mucins ; Chitosan/chemistry ; Drug Delivery Systems ; Stomach
Chemical Substances	Gastric Mucins ; Chitosan (9012-76-4)
Language	English
Publishing date	2024-02-08
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1501516-6
ISSN	1879-1344 ; 0144-8617
ISSN (online)	1879-1344
ISSN	0144-8617
DOI	10.1016/j.carbpol.2024.121926
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